{
  "id": 7454,
  "url": "https://arxiv.org/abs/2603.09108v2",
  "title": "Composed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations",
  "summary": "Medical image retrieval aims to identify clinically relevant lesion cases to support diagnostic decision making, education, and quality control. In practice, retrieval queries often combine a reference lesion image with textual descriptors such as dermoscopic features. We study composed vision-language retrieval for skin cancer, where each query consists of an image to text pair and the database contains biopsy-confirmed, multi-class disease cases. We propose a transformer based framework that l",
  "authors": "Yuheng Wang, Yuji Lin, Jiayue Cai, Z. Jane Wang, Tim K. Lee",
  "category": "research",
  "topics": "safety-alignment,healthcare,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-10T02:42:30.000Z",
  "fetched_at": "2026-07-14T16:33:12.393Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7454",
  "original_url": "https://arxiv.org/abs/2603.09108v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}